Known issues included redundant content, poor search functionality, complex navigation, file storage limitations, and inconsistent content design. There were over 8000 pieces of collateral content and 700 web pages.
We are currently creating a new experience based on user insight collected through detailed research, focus groups, and user testing. Our solution is based on robust user insights gained through immersive discussions and validation sessions as well as comprehensive design and functionality audits.
ML Workstation is a software that sits on top of the user’s computer. Header and search bar appear when activated from an icon on the home screen.
Profile includes a Q/A section that allows users to engage with other Financial Advisors company-wide. Content is rated by other users and scored in the system for relevancy.
Profile includes a Playbook section which allows Financial Advisors to easily save and share items they find valuable. Saves and shares also add value to the content.
Playbooks can contain a wide variety of media types including document files, video, audio and more.
Live-search is enabled to help users quickly find what they’re looking for.
Content contains meta-data which allows for machine-learning and anticipatory design — which is the ability to serve up the best experience possible.
The images that coincide with this case study are the development wireframes created to develop the prototype used to sell the project to upper management.